The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Sell your experiences: a market mechanism based incentive for participatory sensing
Abstract
This paper studies economic models of user participation incentive in participatory sensing applications. User participation is the most important element in participatory sensing applications for providing adequate level of service quality. However, incentive mechanism and its economic model for user participation have never been addressed so far in this research domain. In order to stimulate user participation, we design and evaluate a novel Reverse Auction based Dynamic Price (RADP) incentive mechanism, where users can sell their sensing data to a service provider with users' claimed bid prices. The proposed incentive mechanism focuses on minimizing and stabilizing incentive cost while maintaining adequate number of participants by preventing users from dropping out of participatory sensing applications. Compared with a Random Selection with Fixed Price (RSFP) incentive mechanism, the proposed mechanism not only reduces the incentive cost for retaining same number of participants by more than 60% but also improves the fairness of incentive distribution and social welfare. More importantly, RADP can remove burden of accurate pricing for user sensing data, the most difficult step in RSFP.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
CarTel: a distributed mobile sensor computing system
Hull, B., Bychkovsky, V., Zhang, Y., Chen, K., Goraczko, M., Miu, A., Shih, E., Balakrishnan, H., & Madden, S. (2006) · Proceedings of the 4th international conference on Embedded networked sensor systems · doi:10.1145/1182807.1182821 · Cited by 1,030
Virtual trip lines for distributed privacy-preserving traffic monitoring
Hoh, B., Gruteser, M., Herring, R., Ban, J., Work, D., Herrera, J.-C., Bayen, A. M., Annavaram, M., & Jacobson, Q. (2008) · Proceedings of the 6th international conference on Mobile systems, applications, and services · doi:10.1145/1378600.1378604 · Cited by 351
Self-citationAbdelzaher, T., Anokwa, Y., Boda, P., Burke, J., Estrin, D., Guibas, L., Kansal, A., Madden, S., & Reich, J. (2007) · IEEE Pervasive Computing · doi:10.1109/mprv.2007.38 · Cited by 258
Krause, A., Horvitz, E., Kansal, A., & Zhao, F. (2008) · 2008 International Conference on Information Processing in Sensor Networks (ipsn 2008) · doi:10.1109/ipsn.2008.37 · Cited by 215
How Much is Location Privacy Worth
Danezis, G., Lewis, S. P., & Anderson, R. (2005) · Cited by 163
Cited by
Understanding Human-Machine Networks: A Cross-Disciplinary Survey
Tsvetkova, M., Yasseri, T., Meyer, E. T., Pickering, J. B., Engen, V., Walland, P., Lüders, M., Følstad, A., & Bravos, G. (2018) · ACM Computing Surveys · doi:10.1145/3039868 · Cited by 67
Metadata
- Authors
- Lee, J.-S., & Hoh, B.
- Venue
- 2010 IEEE International Conference on Pervasive Computing and Communications (PerCom)
- Publisher
- IEEE
- Published
- 2010-03
- Pages
- 60-68
- ISSN
- 2474-249X (ISSN-L)
- OpenAlex
- W2088940490
- Cited by
- 396
- References
- 5
- FWCI
- 14.82
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Sell your experiences: a market mechanism based incentive for participatory sensing. https://app.cochat.ai/papers/10.1109/percom.2010.5466993
- The paper
- Lee, J.-S., & Hoh, B. (2010). Sell your experiences: a market mechanism based incentive for participatory sensing. 2010 IEEE International Conference on Pervasive Computing and Communications (PerCom). https://doi.org/10.1109/percom.2010.5466993
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.